Large marketing campaigns rely on massive phone number lists.
But raw datasets are messy.
Before sending messages to 100,000 numbers, we ran a full validation process.
Problems with Raw Phone Lists
Common issues include:
- invalid numbers
- inactive numbers
- duplicated entries
- non-messaging numbers
Step 1 — Import Numbers
Dataset size:
100,000 phone numbers
Step 2 — Normalize Format
Numbers were converted to international format.
Example:
+14158881234
Step 3 — Run a Number Checker
The validation system analyzed:
- number validity
- carrier information
- messaging capability
Validation Results
| Category | Count |
|---|---|
| Valid numbers | 61,000 |
| Invalid numbers | 24,000 |
| Inactive numbers | 15,000 |
Nearly 39% of the list was unusable.
Campaign Results After Cleaning
After filtering invalid numbers:
- delivery rates increased
- response rates improved
- marketing costs dropped
Conclusion
Cleaning phone lists before messaging campaigns is essential.
A number checker ensures that campaigns reach real users.
Try bulk validation here:
[https://numberchecker.ai/?utm_source=google&utm_medium=organic&utm_campaign=DEVSY3.13]